Structure prediction in Materials Science and Characterisation with EELS in the low-loss regime

Lead Research Organisation: University of Oxford
Department Name: Materials


This project is to enable new developments to the CASTEP Density Functional Theory (DFT) code to provide accurate low loss EELS (Electron Energy Loss Spectra). This necessary to interpret high resolution measurements made possible with the latest generation of Scanning Transmission Electron Microscopes (STEM). This includes the EPSRC National Facility for Aberration-Corrected Scanning Transmission Electron Microscopy (SuperSTEM) located at Daresbury Laboratories. Together, the combination of quantum mechanical DFT calculations and STEM measurements present a powerful tool for materials characterisation. Work in the last decade has shown that it is now possible to use techniques based on quantum mechanics to predict the structure of hitherto unknown materials. To identify the existence of such materials in nature requires the use of experimental techniques such as EELS, which can be compared to the spectra predicted for the proposed structure from DFT simulations. By enhancing our ability to predict low-loss EELS this project will both expand the range of materials systems we can study, and the certainty and confidence with which we can make predictions. The project will enable simulations of a number of materials systems of importance to future materials and the energy sector; including zirconium oxides used in the nuclear industry, fuel cells, Li based batteries and catalysts.

The CASTEP code is developed by academics at the Universities of Cambridge, Oxford, York, Durham and Royal Holloway (London). It is freely available to UK academics and a supported commercial version is marketed by Dassault Systèmes / BIOVIA (with UK HQ in Cambridge). They provide support to industrial users across a wide variety of sectors including: pharmaceuticals, catalysis, energy.

This project delivers new capabilities to accelerate the development of novel materials, particularly for energy applications. However, note that the general nature of quantum-mechanical modelling means tht the tools can be applied to a very wide range of materials. In the first instance the beneficiary is the UK company Johnson-Matthey who will supply experimental data on catalysts and fuel cell materials. Through this project they will enhance their understanding of the structure and composition of these materials. However, by working with a leading scientific software company (Dassault Systèmes / BIOVIA) we ensure that the tools developed will be made available across Materials sector - ensuring maximum impact.

The Themes are:

Physical sciences


10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R512333/1 01/10/2017 30/09/2021
2109852 Studentship EP/R512333/1 01/10/2017 30/09/2021 Xinlei Liu